code: def create_action_features(in_frames, out_frames):
      features = create_basic_features(in_frames, out_frames)
      x = np.random.randint(0, 5, size=(8, in_frames, 1))
      y = np.random.randint(0, 5, size=(8, out_frames, 1))
      features["input_action"] = tf.constant(x, dtype=tf.int32)
      features["target_action"] = tf.constant(y, dtype=tf.int32)
      return features
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  from tensor2tensor.data_generators import video_generated
  from tensor2tensor.layers import modalities
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 5 for calling a global function with example usage: create_action_features(in_frames, out_frames) and returns: features